한글목차

세계 AI 비전 칩 시장의 미래는 보안 및 감시, 자동차, 가전, IoT, 드론, 로봇 시장에 기회가 있어 유망한 것으로 전망되고 있습니다. 세계 AI 비전 칩 시장은 2025-2031년 연평균 복합 성장률(CAGR) 32.4%로 성장할 것으로 예상됩니다. 이 시장의 주요 촉진요인은 엣지 컴퓨팅의 채택이 확대되고 있으며, 제조, 의료, 보안, 자율주행차 등 다양한 산업에서 컴퓨터 비전 기술의 채택이 증가하고 있다는 점입니다.

• Lucintel의 예측에 따르면, 유형별로는 12nm가 예측 기간 동안 가장 높은 성장세를 보일 것으로 예상됩니다.
• 용도별로는 보안 및 감시 분야가 가장 높은 성장이 예상되고 있습니다.
• 지역별로는 아시아태평양이 예측 기간 동안 가장 높은 성장을 보일 것으로 예상됩니다.

AI 비전 칩 시장의 전략적 성장 기회

AI 비전 칩 시장은 기술 발전과 시장 수요에 힘입어 다양한 용도에서 전략적 성장 기회를 제공합니다.

• 스마트 보안 시스템: 스마트 보안 시스템의 성장은 AI 비전 칩에 큰 기회를 제공합니다. 이 칩은 얼굴 인식, 움직임 감지, 이상 감지 등의 기능을 통해 감시 카메라 및 보안 솔루션을 강화합니다. 주거, 상업 및 공공 부문의 고급 보안 솔루션에 대한 수요가 이 응용 분야의 성장을 가속하고 있습니다.
• 자율주행차: 자율주행차는 AI 비전 칩의 주요 성장 분야입니다. 이 칩은 내비게이션, 장애물 감지, 운전 보조 시스템에 사용되는 시각 데이터 처리에 필수적이기 때문입니다. 현재 진행 중인 자율주행 기술 개발과 자동차 안전 기능의 발전은 자동차 산업에서 AI 비전 칩의 기회를 창출하고 있습니다.
• 산업 자동화: AI 비전 칩은 품질 관리, 예지보전, 로봇 공학 등의 용도로 산업 자동화 분야에서 점점 더 많이 사용되고 있습니다. 이 칩은 제조 공정의 정확성과 효율성을 향상시켜 스마트 팩토리와 자동 생산 라인의 성장을 가속하고 있습니다. 인더스트리 4.0과 자동화에 대한 관심이 이 시장 부문을 확대시키고 있습니다.
• 의료 및 의료 영상: 의료 분야에서는 의료용 영상 처리 및 진단에 AI 비전 칩의 기회가 있습니다. 이 칩은 이미지 품질 향상, 실시간 분석, 패턴 인식 등의 기능으로 이미지 처리 시스템을 강화합니다. 고급 진단 도구 및 원격 의료에 대한 수요가 증가함에 따라 이 분야에서의 채택이 가속화되고 있습니다.
• 증강현실(AR) 및 가상현실(VR) : AI 비전 칩은 AR 및 VR 용도에 필수적이며, 몰입감 있는 경험과 실시간 상호 작용에 필요한 처리 능력을 제공합니다. 신흥국의 AR 및 VR 기술 시장의 발전은 게임, 교육, 엔터테인먼트 등의 용도를 지원하는 AI 비전 칩의 기회를 창출하고 사용자 경험을 향상시키며 시장 잠재력을 확장하고 있습니다.

이러한 전략적 성장 기회는 AI 비전 칩의 다양한 응용 분야와 잠재력을 부각시키고 있습니다. 스마트 보안 시스템, 자율주행차, 산업 자동화, 의료, AR/VR에 집중함으로써 기업들은 확대되는 시장에 진입하고 새로운 수요에 대응할 수 있으며, AI 비전 칩 분야의 혁신과 성장을 가속할 수 있습니다.

AI 비전 칩 시장 활성화 요인 및 과제

AI 비전 칩 시장은 기술 발전, 경제적 요인, 규제적 고려사항 등 다양한 촉진요인 및 과제에 의해 형성되고 있습니다.

AI 비전 칩 시장 성장 촉진요인으로는 다음과 같은 것들이 있습니다.

• 기술 발전: AI와 비전 기술의 급속한 발전이 AI 비전 칩 시장을 주도하고 있습니다. 칩 설계, 처리 능력, AI 알고리즘의 혁신은 비전 시스템의 기능을 강화하여 보다 진보되고 효율적인 용도를 가능하게 하고 있습니다. 이러한 발전은 여러 산업 분야에서 AI 비전 칩의 성장을 뒷받침하고 있습니다.
• 자동화 수요 증가: 제조, 자동차, 보안 등의 분야에서 자동화 수요가 증가함에 따라 AI 비전 칩의 채택이 증가하고 있습니다. 이 칩은 고도의 시각적 인식과 처리를 통해 자동화 노력을 지원하고 효율성을 향상시킬 수 있습니다. 스마트 팩토리, 자율주행차, 지능형 보안 시스템에 대한 관심이 시장 성장을 견인하고 있습니다.
• 소비자 가전제품의 확대: 스마트폰, 스마트홈 기기 등 소비자 가전제품에 AI 비전 칩을 통합하는 것이 시장 확대의 원동력이 되고 있습니다. 소비자 제품의 이미지 처리 기능 강화 및 지능형 기능에 대한 수요는 AI 비전 칩 제조업체에게 기회를 제공합니다. 이러한 추세는 일상 기기에서 첨단 비전 기술이 점점 더 중요해지고 있음을 반영하고 있습니다.
• 스마트 시티 및 인프라 성장: 스마트 시티 및 인프라 개발은 감시, 교통 관리, 공공 안전 등의 용도에 AI 비전 칩에 대한 수요를 창출하고 있습니다. 지능형 및 커넥티드 도시 환경 구축에 대한 관심은 이러한 노력을 지원하는 비전 칩의 채택을 촉진하여 시장 성장에 기여하고 있습니다.
• 엣지 컴퓨팅의 발전: 엣지 컴퓨팅의 부상은 로컬 처리 기능을 갖춘 AI 비전 칩에 대한 수요를 촉진하고 있습니다. 엣지 AI 칩은 실시간 데이터 분석 및 응답을 가능하게 하여 자율주행차, 산업 자동화, 스마트 기기 용도를 지원합니다. 이러한 추세는 효율적이고 지연 시간이 짧은 컴퓨팅 솔루션에 대한 수요 증가를 반영하고 있습니다.

AI 비전 칩 시장의 과제는 다음과 같습니다:

• 높은 개발 비용: AI 비전 칩의 개발 및 생산에는 연구, 설계, 제조와 관련된 높은 비용이 소요됩니다. 이러한 비용은 신규 시장 진출기업에게는 진입장벽이 되고, 최종 사용자에게는 칩의 가격 경쟁력에 영향을 미칩니다. 경쟁력 있는 가격을 유지하면서 개발 비용을 관리하는 것은 업계에서 중요한 과제입니다.
• 통합 및 호환성 문제: AI 비전 칩을 다양한 용도 및 시스템에 배포할 때 통합 및 호환성 문제가 발생할 수 있습니다. 칩이 다양한 하드웨어 및 소프트웨어 플랫폼과 원활하게 작동하도록 하는 것은 성공적인 구현을 위해 필수적입니다. 이러한 문제를 해결하기 위해서는 상호운용성을 위한 세심한 설계와 테스트가 필요합니다.
• 데이터 프라이버시 및 보안 문제: AI 비전 칩은 감시, 의료 등 민감한 용도에 사용되기 때문에 데이터 프라이버시 및 보안에 대한 우려는 중요한 문제입니다. 데이터를 보호하고 사용자의 신뢰를 유지하기 위해서는 강력한 보안 조치와 규제 준수를 보장하는 것이 매우 중요합니다. 비전 기술의 보급을 위해서는 이러한 우려에 대한 대응이 필수적입니다.

AI 비전 칩 시장은 기술 발전, 자동화 수요, 가전제품의 성장, 스마트 시티 개발, 엣지 컴퓨팅의 영향을 받고 있습니다. 그러나 높은 개발 비용, 통합 문제, 데이터 보안 문제 등은 AI 비전 칩 시장의 지속적인 성장과 혁신을 위해서는 이러한 시장 성장 촉진요인과 과제의 균형을 맞추는 것이 중요합니다.

목차

제1장 주요 요약

제2장 세계의 AI 비전 칩 시장 : 시장 역학

• 서론, 배경, 분류
• 공급망
• 업계 촉진요인과 과제

제3장 시장 동향과 예측 분석(2019-2031년)

• 거시경제 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 AI 비전 칩 시장 동향(2019-2024년)과 예측(2025-2031년)
• 세계의 AI 비전 칩 시장 : 유형별
  • 12nm
  • 14nm
  • 22nm
  • 기타
• 세계의 AI 비전 칩 시장 : 용도별
  • 보안 및 감시
  • 자동차
  • 가전
  • 사물인터넷(IoT)
  • 드론
  • 로봇
  • 기타

제4장 지역별 시장 동향과 예측 분석(2019-2031년)

• 세계의 AI 비전 칩 시장 : 지역별
• 북미의 AI 비전 칩 시장
• 유럽의 AI 비전 칩 시장
• 아시아태평양의 AI 비전 칩 시장
• 기타 지역의 AI 비전 칩 시장

제5장 경쟁 분석

• 제품 포트폴리오 분석
• 운영 통합
• Porter의 Five Forces 분석

제6장 성장 기회와 전략 분석

• 성장 기회 분석
  • 세계의 AI 비전 칩 시장 성장 기회 : 유형별
  • 세계의 AI 비전 칩 시장 성장 기회 : 용도별
  • 세계의 AI 비전 칩 시장 성장 기회 : 지역별
• 세계 AI 비전 칩 시장의 새로운 동향
• 전략적 분석
  • 신제품 개발
  • 세계의 AI 비전 칩 시장 생산능력 확대
  • 세계 AI 비전 칩 시장에서의 인수합병(M&A) 및 합작투자(JV)
  • 인증 및 라이선싱

제7장 주요 기업 개요

• Ambarella
• Nextchip
• Centeye
• Ambarella
• Axera
• Goke Microelectronics
• PixelCore
• HiSilicon
• IMICRO
• NextVPU

영문목차

The future of the global AI vision chip market looks promising with opportunities in the security & surveillance, automotive, consumer electronic, internet of things, drone, and robot markets. The global AI vision chip market is expected to grow with a CAGR of 32.4% from 2025 to 2031. The major drivers for this market are the growing adoption of edge computing and the rising adoption of computer vision technology in various industries such as manufacturing, healthcare, security, and autonomous vehicles.

• Lucintel forecasts that, within the type category, 12 nm is expected to witness the highest growth over the forecast period.
• Within the application category, security & surveillance is expected to witness the highest growth.
• In terms of regions, APAC is expected to witness the highest growth over the forecast period.

Gain valuable insights for your business decisions with our comprehensive 150+ page report.

Emerging Trends in the AI Vision Chip Market

The AI vision chip market is evolving with several key trends that are driving innovation and adoption across various applications.

• Edge AI Integration: Edge AI integration is a significant trend, enabling AI vision chips to process data locally rather than relying on cloud computing. This reduces latency, enhances real-time processing, and improves privacy by minimizing data transmission. Edge AI chips are crucial for applications such as autonomous vehicles, smart cameras, and industrial automation, where immediate data analysis and response are essential.
• Enhanced Energy Efficiency: There is a growing emphasis on energy-efficient AI vision chips to address the increasing demand for power in high-performance computing. Advances in chip design and manufacturing technologies are leading to the development of chips that consume less power while delivering high performance. This trend supports the deployment of AI vision chips in battery-powered devices and applications where energy conservation is critical.
• Increased Focus on Security and Privacy: As AI vision chips are used in sensitive applications like surveillance and personal devices, there is an increased focus on enhancing security and privacy features. Innovations include incorporating advanced encryption and secure data processing capabilities directly into the chips. This trend aims to address concerns about data breaches and unauthorized access, ensuring the secure and reliable operation of vision systems.
• Integration with 5G Networks: The integration of AI vision chips with 5G networks is enhancing the capabilities of remote and real-time applications. 5G's high-speed connectivity and low latency complement the processing power of AI vision chips, enabling advanced use cases such as real-time remote monitoring, smart city infrastructure, and augmented reality applications. This trend supports the growth of connected devices and applications requiring high-speed data transfer.
• Growth of AI-Powered Robotics: AI-powered robotics is a key growth area for AI vision chips, as these chips enhance the visual perception and decision-making capabilities of robots. Developments include improved object recognition, depth perception, and navigation capabilities. This trend supports advancements in various robotics applications, including manufacturing, healthcare, and service robots, driving innovation in automation and intelligent systems.

These emerging trends are reshaping the AI vision chip market by enhancing performance, efficiency, and application capabilities. Edge AI integration, energy efficiency, security and privacy, 5G connectivity, and AI-powered robotics are driving innovation and adoption, leading to more advanced and versatile vision systems.

Recent Developments in the AI Vision Chip Market

Recent developments in the AI vision chip market reflect advancements in technology and increasing demand for sophisticated imaging solutions.

• Introduction of High-Performance Edge AI Chips: New high-performance edge AI chips are being introduced, offering advanced processing capabilities for real-time image analysis. These chips are designed to perform complex tasks locally, reducing latency and enhancing the functionality of applications such as autonomous vehicles and smart cameras. The focus is on improving processing power while maintaining low energy consumption.
• Advancements in Low-Power AI Vision Chips: Developments in low-power AI vision chips are addressing the need for energy efficiency in battery-operated devices. Innovations include optimizing chip architectures and using advanced manufacturing processes to reduce power consumption without compromising performance. These chips are essential for wearable devices, IoT applications, and portable imaging systems.
• Enhanced AI Algorithms for Vision Chips: The integration of advanced AI algorithms into vision chips is improving capabilities such as object detection, facial recognition, and scene understanding. These enhancements enable more accurate and sophisticated image processing, supporting applications in security, robotics, and augmented reality. AI-driven improvements are making vision chips more effective in diverse and complex environments.
• Expansion of AI Vision Chips in Consumer Electronics: AI vision chips are increasingly being integrated into consumer electronics, such as smartphones and smart home devices. Developments include enhancing camera systems with advanced image processing capabilities and enabling new features such as real-time image enhancement and object recognition. This trend reflects the growing demand for intelligent and feature-rich consumer products.
• Growth in AI Vision Chips for Automotive Applications: The automotive sector is experiencing growth in AI vision chips designed for advanced driver-assistance systems (ADAS) and autonomous vehicles. Innovations include chips that support features such as lane-keeping, collision avoidance, and adaptive cruise control. These developments are driving advancements in automotive safety and automation, reflecting the industry's focus on intelligent transportation solutions.

These key developments highlight the rapid advancements in the AI vision chip market. High-performance edge AI chips, low-power solutions, enhanced AI algorithms, expansion into consumer electronics, and growth in automotive applications are driving innovation and shaping the future of AI vision technologies.

Strategic Growth Opportunities for AI Vision Chip Market

The AI vision chip market presents several strategic growth opportunities across various applications, driven by technological advancements and market demands.

• Smart Security Systems: The growth of smart security systems offers significant opportunities for AI vision chips. These chips enhance surveillance cameras and security solutions with capabilities such as facial recognition, motion detection, and anomaly detection. The demand for advanced security solutions in residential, commercial, and public sectors is driving growth in this application area.
• Autonomous Vehicles: Autonomous vehicles are a major growth area for AI vision chips, as these chips are critical for processing visual data used in navigation, obstacle detection, and driver assistance systems. The ongoing development of self-driving technology and advancements in automotive safety features are creating opportunities for AI vision chips in the automotive industry.
• Industrial Automation: AI vision chips are increasingly being used in industrial automation for applications such as quality control, predictive maintenance, and robotics. These chips improve the accuracy and efficiency of manufacturing processes, driving growth in smart factories and automated production lines. The focus on Industry 4.0 and automation is expanding this market segment.
• Healthcare and Medical Imaging: The healthcare sector presents opportunities for AI vision chips in medical imaging and diagnostics. These chips enhance imaging systems with capabilities such as improved image quality, real-time analysis, and pattern recognition. The growing demand for advanced diagnostic tools and telemedicine is driving adoption in this application area.
• Augmented Reality (AR) and Virtual Reality (VR): AI vision chips are crucial for AR and VR applications, providing the processing power needed for immersive experiences and real-time interactions. Developments in AR and VR technologies are creating opportunities for AI vision chips to support applications in gaming, training, and entertainment, enhancing user experiences and expanding market potential.

These strategic growth opportunities highlight the diverse applications and potential of AI vision chips. By focusing on smart security systems, autonomous vehicles, industrial automation, healthcare, and AR/VR, companies can tap into expanding markets and address emerging needs, driving innovation and growth in the AI vision chip sector.

AI Vision Chip Market Driver and Challenges

The AI vision chip market is shaped by various drivers and challenges, including technological advancements, economic factors, and regulatory considerations.

The factors responsible for driving the AI vision chip market include:

• Technological Advancements: Rapid advancements in AI and vision technologies are driving the AI vision chip market. Innovations in chip design, processing power, and AI algorithms are enhancing the capabilities of vision systems, enabling more sophisticated and efficient applications. These advancements support the growth of AI vision chips across multiple industries.
• Increasing Demand for Automation: The growing demand for automation in sectors such as manufacturing, automotive, and security is driving the adoption of AI vision chips. These chips enable advanced visual recognition and processing, supporting automation efforts and improving efficiency. The focus on smart factories, autonomous vehicles, and intelligent security systems fuels market growth.
• Expansion of Consumer Electronics: The integration of AI vision chips into consumer electronics, such as smartphones and smart home devices, is driving market expansion. The demand for enhanced imaging capabilities and intelligent features in consumer products is creating opportunities for AI vision chip manufacturers. This trend reflects the increasing importance of advanced vision technologies in everyday devices.
• Growth in Smart Cities and Infrastructure: The development of smart cities and infrastructure is creating demand for AI vision chips in applications such as surveillance, traffic management, and public safety. The focus on building intelligent and connected urban environments is driving the adoption of vision chips that support these initiatives, contributing to market growth.
• Advances in Edge Computing: The rise of edge computing is driving demand for AI vision chips with local processing capabilities. Edge AI chips enable real-time data analysis and response, supporting applications in autonomous vehicles, industrial automation, and smart devices. This trend reflects the growing need for efficient and low-latency computing solutions.

Challenges in the AI vision chip market include:

• High Development Costs: The development and production of AI vision chips involve high costs related to research, design, and manufacturing. These expenses can be a barrier to entry for new players and impact the affordability of chips for end users. Managing development costs while maintaining competitive pricing is a key challenge for the industry.
• Integration and Compatibility Issues: Integration and compatibility issues can arise when deploying AI vision chips in diverse applications and systems. Ensuring that chips work seamlessly with different hardware and software platforms is essential for successful implementation. Addressing these challenges requires careful design and testing to achieve interoperability.
• Data Privacy and Security Concerns: As AI vision chips are used in sensitive applications such as surveillance and healthcare, data privacy and security concerns are significant challenges. Ensuring robust security measures and compliance with regulations is crucial to protect data and maintain user trust. Addressing these concerns is essential for the widespread adoption of vision technologies.

The AI vision chip market is influenced by technological advancements, automation demand, consumer electronics growth, smart city development, and edge computing. However, high development costs, integration issues, and data security concerns present challenges. Balancing these drivers and challenges is crucial for the continued growth and innovation in the AI vision chip market.

List of AI Vision Chip Companies

Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. Through these strategies AI vision chip companies cater increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the AI vision chip companies profiled in this report include-

• Ambarella
• Nextchip
• Centeye
• Ambarella
• Axera
• Goke Microelectronics
• PixelCore
• HiSilicon
• IMICRO
• NextVPU

AI Vision Chip by Segment

The study includes a forecast for the global AI vision chip market by type, application, and region.

AI Vision Chip Market by Type [Analysis by Value from 2019 to 2031]:

• 12 nm
• 14 nm
• 22 nm
• Others

AI Vision Chip Market by Application [Analysis by Value from 2019 to 2031]:

• Security & Surveillance
• Automotive
• Consumer Electronics
• Internet of Things
• Drone
• Robot
• Others

AI Vision Chip Market by Region [Analysis by Value from 2019 to 2031]:

• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the AI Vision Chip Market

The AI vision chip market has experienced significant advancements due to increasing demand for enhanced visual recognition and processing capabilities across various sectors. AI vision chips, which integrate artificial intelligence with imaging technologies, are driving innovations in automation, surveillance, automotive, and consumer electronics. Each country is making strides in this technology, reflecting local priorities and technological expertise.

• United States: In the U.S., recent developments in AI vision chips include advancements in edge computing and integration with AI platforms for real-time image processing. Companies like Intel and NVIDIA are leading innovations with chips designed for high-performance computer vision tasks, supporting applications in autonomous vehicles, security systems, and augmented reality (AR). The focus is also on enhancing chip efficiency and processing power to meet growing demands in data-intensive applications.
• China: China is rapidly advancing in the AI vision chip market with significant investments in AI research and development. Chinese tech giants such as Huawei and Alibaba are developing vision chips that enhance capabilities in facial recognition, smart surveillance, and industrial automation. The government's push for technological self-sufficiency and advancements in semiconductor manufacturing is accelerating the deployment of AI vision chips across various sectors, including smart cities and e-commerce.
• Germany: Germany is focusing on integrating AI vision chips with industrial automation and smart manufacturing. Companies like Bosch and Infineon are developing chips that enhance machine vision systems, enabling precision in manufacturing processes and predictive maintenance. The emphasis is on improving energy efficiency and processing speed to support Germany's strong industrial base and its Industry 4.0 initiatives, driving innovation in smart factories and automation systems.
• India: In India, the AI vision chip market is growing with applications in security, retail, and healthcare. Indian startups and tech companies are focusing on cost-effective solutions that leverage AI vision chips for surveillance systems, automated retail checkout, and medical imaging. The market is driven by increasing urbanization and the need for advanced technology in growing sectors, along with government initiatives to promote digital transformation and innovation.
• Japan: Japan is advancing AI vision chips with applications in robotics, consumer electronics, and smart infrastructure. Companies such as Sony and Panasonic are developing chips that enhance image quality and processing capabilities for robotics and smart home devices. Japan's focus on integrating AI with IoT technologies is driving innovations in automation and smart city applications, reflecting the country's commitment to leading in technology and digital transformation.

Features of the Global AI Vision Chip Market

Market Size Estimates: AI vision chip market size estimation in terms of value ($B).

Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.

Segmentation Analysis: AI vision chip market size by type, application, and region in terms of value ($B).

Regional Analysis: AI vision chip market breakdown by North America, Europe, Asia Pacific, and Rest of the World.

Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the AI vision chip market.

Strategic Analysis: This includes M&A, new product development, and competitive landscape of the AI vision chip market.

Analysis of competitive intensity of the industry based on Porter's Five Forces model.

If you are looking to expand your business in this market or adjacent markets, then contact us. We have done hundreds of strategic consulting projects in market entry, opportunity screening, due diligence, supply chain analysis, M & A, and more.

This report answers following 11 key questions:

• Q.1. What are some of the most promising, high-growth opportunities for the AI vision chip market by type (12 nm, 14 nm, 22 nm, and others), application (security & surveillance, automotive, consumer electronics, internet of things, drone, robot, and others), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
• Q.2. Which segments will grow at a faster pace and why?
• Q.3. Which region will grow at a faster pace and why?
• Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
• Q.5. What are the business risks and competitive threats in this market?
• Q.6. What are the emerging trends in this market and the reasons behind them?
• Q.7. What are some of the changing demands of customers in the market?
• Q.8. What are the new developments in the market? Which companies are leading these developments?
• Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
• Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
• Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

Table of Contents

1. Executive Summary

2. Global AI Vision Chip Market : Market Dynamics

• 2.1: Introduction, Background, and Classifications
• 2.2: Supply Chain
• 2.3: Industry Drivers and Challenges

3. Market Trends and Forecast Analysis from 2019 to 2031

• 3.1. Macroeconomic Trends (2019-2024) and Forecast (2025-2031)
• 3.2. Global AI Vision Chip Market Trends (2019-2024) and Forecast (2025-2031)
• 3.3: Global AI Vision Chip Market by Type
  • 3.3.1: 12 nm
  • 3.3.2: 14 nm
  • 3.3.3: 22 nm
  • 3.3.4: Others
• 3.4: Global AI Vision Chip Market by Application
  • 3.4.1: Security & Surveillance
  • 3.4.2: Automotive
  • 3.4.3: Consumer Electronics
  • 3.4.4: Internet of Things
  • 3.4.5: Drone
  • 3.4.6: Robot
  • 3.4.7: Others

4. Market Trends and Forecast Analysis by Region from 2019 to 2031

• 4.1: Global AI Vision Chip Market by Region
• 4.2: North American AI Vision Chip Market
  • 4.2.1: North American Market by Type: 12 nm, 14 nm, 22 nm, and Others
  • 4.2.2: North American Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
• 4.3: European AI Vision Chip Market
  • 4.3.1: European Market by Type: 12 nm, 14 nm, 22 nm, and Others
  • 4.3.2: European Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
• 4.4: APAC AI Vision Chip Market
  • 4.4.1: APAC Market by Type: 12 nm, 14 nm, 22 nm, and Others
  • 4.4.2: APAC Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others
• 4.5: ROW AI Vision Chip Market
  • 4.5.1: ROW Market by Type: 12 nm, 14 nm, 22 nm, and Others
  • 4.5.2: ROW Market by Application: Security & Surveillance, Automotive, Consumer Electronics, Internet of Things, Drone, Robot, and Others

5. Competitor Analysis

• 5.1: Product Portfolio Analysis
• 5.2: Operational Integration
• 5.3: Porter's Five Forces Analysis

6. Growth Opportunities and Strategic Analysis

• 6.1: Growth Opportunity Analysis
  • 6.1.1: Growth Opportunities for the Global AI Vision Chip Market by Type
  • 6.1.2: Growth Opportunities for the Global AI Vision Chip Market by Application
  • 6.1.3: Growth Opportunities for the Global AI Vision Chip Market by Region
• 6.2: Emerging Trends in the Global AI Vision Chip Market
• 6.3: Strategic Analysis
  • 6.3.1: New Product Development
  • 6.3.2: Capacity Expansion of the Global AI Vision Chip Market
  • 6.3.3: Mergers, Acquisitions, and Joint Ventures in the Global AI Vision Chip Market
  • 6.3.4: Certification and Licensing

7. Company Profiles of Leading Players

• 7.1: Ambarella
• 7.2: Nextchip
• 7.3: Centeye
• 7.4: Ambarella
• 7.5: Axera
• 7.6: Goke Microelectronics
• 7.7: PixelCore
• 7.8: HiSilicon
• 7.9: IMICRO
• 7.10: NextVPU